The Block · T5 Evals & reliability

Evals vs benchmarks

Last reviewed 21 Oct 2026by Pratima Chainani

A benchmark is a public test that ranks models on shared tasks. An eval is your own repeatable test set, built from your real work, that tells you whether a model or a change actually helps you.

Leaderboards disagree. The State of AI Report 2026 notes that different rankings crown different leaders: Anthropic leads the Artificial Analysis Intelligence Index while Google leads LMArena’s preference ranking.

Developers trust what they can check. In Stack Overflow’s 2026 Developer Survey, 48% say they trust AI when they can easily validate its answers.

So a top benchmark score is a reason to test a model, not a reason to switch to it. Your evals decide.

Common misread

It topped the leaderboard, so it’ll be best for us.

It’s best on that leaderboard’s tasks. Test it on yours.

For your code

Write evals from real tickets and run them in CI before you switch models or prompts.

For your roadmap

Make “passes our evals” the bar for any model or vendor change, not a leaderboard rank.

Sources

  1. State of AI Report 2026, Air Street Capital · 8 Oct 2026
  2. Stack Overflow Developer Survey 2026, AI · Oct 2026